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Internship Machine Vision Engineer Jobs in Franklin, MA

SICK AG

Software Engineer II

Canton, MA · On-site

$80 - $100/hr

Machine Vision, Algorithms & Emerging Technologies * Design, implement, and optimize classical and ... Perform full engineering responsibilities including estimation, requirement analysis, technical ...

Delsys

R&D Software Engineer (FT)

Natick, MA · On-site

$90K - $110K/yr

Software Engineers in this role will focus on building robust backend systems, embedded processing ... computer vision, and machine learning pipelines for wearable and non-contact sensors. • ...

Tristar AI, Inc.

Hardware Engineer

Cambridge, MA · On-site

$100 - $125/hr

Qualifications * 5+ years of experience in hardware engineering, systems integration, or solution architecture involving machine vision systems. * Strong working knowledge of industrial cameras (e.g ...

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All JobsMachine Vision Engineer JobsInternship Machine Vision Engineer JobsInternship Machine Vision Engineer Jobs in Franklin, MA

Internship Machine Vision Engineer information

See Franklin, MA salary details

$13

$25

$39

How much do internship machine vision engineer jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for internship machine vision engineer in Franklin, MA is $25.69, according to ZipRecruiter salary data. Most workers in this role earn between $20.91 and $29.13 per hour, depending on experience, location, and employer.

What does an internship machine vision engineer do?

An Internship Machine Vision Engineer assists in developing and implementing computer vision algorithms to enable machines or robots to interpret visual data. Their tasks often include image processing, object detection, camera calibration, and working with various sensors. Interns typically support senior engineers in testing, data collection, and model optimization, gaining hands-on experience with real-world applications. This role offers valuable exposure to fields like automation, robotics, and artificial intelligence, helping interns build a foundation for a career in machine vision.

What types of projects do internship machine vision engineers typically work on, and how do they collaborate within the team?

As an Internship Machine Vision Engineer, you will often be involved in projects that focus on developing and testing computer vision algorithms, working with image processing tools, and supporting the integration of machine vision systems into larger automation solutions. You’ll collaborate closely with senior engineers, software developers, and sometimes hardware teams to validate solutions and troubleshoot issues. Regular meetings, code reviews, and shared project management tools help ensure smooth communication and learning opportunities, fostering both technical growth and teamwork.

What are the key skills and qualifications needed to thrive as an internship machine vision engineer, and why are they important?

To thrive as an Internship Machine Vision Engineer, you generally need a background in computer science, electrical engineering, or a related field, with foundational knowledge in image processing and computer vision algorithms. Familiarity with programming languages such as Python or C++, experience with tools like OpenCV, and exposure to machine learning frameworks are typically required. Strong problem-solving abilities, attention to detail, and effective teamwork are the soft skills that set outstanding candidates apart. These competencies are crucial for efficiently developing, testing, and deploying vision solutions that address real-world automation and inspection challenges.

What cities near Franklin, MA are hiring for Internship Machine Vision Engineer jobs?

Cities near Franklin, MA with the most Internship Machine Vision Engineer job openings:

Internship Machine Vision Engineer jobs near you

Computer Vision / Machine Learning Engineer

Boston, MA • On-site

AIToolboard
See more jobs at AIToolboardexternal

$100 - $125/hr

Other

Re-posted 4 days ago

Job description

Jobs / Computer Vision / Machine Learning Engineer

Computer Vision / Machine Learning Engineer

Contractor

About the Role

Computer Vision / Machine Learning Engineer (Contract)Contract Length: 6 monthsWork Arrangement: Hybrid (onsite 3 days/week in Greater Boston)Computer Vision / Machine Learning Engineer to support an active, production-focused initiative. This role is centered on improving detection and tracking accuracy for object-counting systems operating in real-world, high-throughput environments.The ideal candidate has hands-on experience building and deploying computer vision models, working with multimodal sensor data, and optimizing inference pipelines for edge deployment.

What You’ll Work On
  • Enhancing object detection, segmentation, and tracking accuracy in operational systems
  • Developing and deploying models into validation and pre-production environments
  • Improving real-time performance and reliability on edge hardware
Key Responsibilities
  • Model Development: Train, validate, and deploy computer vision models, with an emphasis on instance segmentation
  • Tracking & Fusion: Implement tracking approaches that combine color and depth data to maintain object persistence across frames
  • Data Quality: Support data curation efforts and audit external annotations to ensure high-quality ground truth
  • Performance Optimization: Tune inference pipelines for low-latency execution on edge platforms
Technical Environment
  • Computer Vision & ML: Instance Segmentation, Object Tracking
  • Sensor Data: RGB + Depth (basic multi-sensor fusion)
  • Edge & Optimization: NVIDIA-based edge hardware, TensorRT or similar acceleration tools
Qualifications
  • Proven experience delivering production-grade ML or CV systems
  • Strong software engineering fundamentals (version control, testing, CI/CD)
  • Experience deploying models beyond experimentation into real environments
  • Ability to meet strict accuracy and performance benchmarks
  • Comfortable working within cloud-only data environments with controlled access policies
Nice to Have
  • Experience optimizing models for edge or embedded systems
  • Familiarity with real-time or near–real-time vision pipelines
  • Background in industrial, robotics, or high-volume operational settings
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